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Found 147 Skills
PlutoBa platform help — AI influencer vetting and creator due diligence across TikTok, Instagram, and YouTube. Covers PlutoBa Score (7-dimension assessment), Deep Assessments (100+ posts, 300+ comments), fake follower detection, audience authenticity, brand safety risk scoring, rate benchmarking, AI-powered creator outreach, creator CRM, and campaign briefs. Use when worried an influencer's followers are fake, need to check if a creator is brand-safe before signing a deal, want to know what to pay an influencer, PlutoBa Score seems too low or too high, creator outreach templates aren't getting responses, unsure which PlutoBa plan fits your needs, or setting up PlutoBa for an agency with multiple brands. Do NOT use for influencer strategy across platforms (use /sales-influencer-marketing) or influencer discovery and search (use /sales-hypeauditor or /sales-modash).
Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.
Structurally deconstruct competitors from four dimensions: strategy, functionality, experience, and growth, and output referenceable points, non-replicable points, and differentiation suggestions. Use this Skill when users say "competitor analysis", "competitor deconstruction", "help me analyze competitors", "take a look at these competitors", "compare with competitors", "benchmarking analysis", "how to do differentiation", or when users provide a list of competitors and require systematic analysis. Also applicable for: users upload competitor screenshots/links/experience reports and require structured deconstruction; users require comparison of gaps between their own products and competitors; users want to find differentiation entry points. Not applicable for: pure requirement document writing (use prd-writer), pure priority sorting (use prioritization-engine), pure user research design (use survey-designer).
Track and analyze content performance across Instagram, YouTube, LinkedIn, Twitter/X, and Reddit using anysite MCP server. Measure engagement metrics, analyze post effectiveness, benchmark content strategy, identify top-performing content, and optimize posting strategies. Supports post performance tracking, engagement analysis, content type comparison, and competitive benchmarking. Use when users need to measure content ROI, optimize social strategy, identify viral content patterns, or analyze content engagement across platforms.
Conduct compensation benchmarking analysis to position salaries against market data. Use this skill when the user needs to assess pay competitiveness, build salary bands, or analyze pay equity — even if they say 'are we paying market rate', 'salary benchmarking', or 'compensation analysis'.
Guide for creating, improving, benchmarking, and packaging Claude Agent Skills (SKILL.md files). Invoke when users want to create a skill from scratch, improve or test an existing skill, benchmark skill performance with variance analysis, or optimize a skill description for triggering accuracy. Also invoke when users say "turn this into a skill", "make a skill for X", "help me write a SKILL.md", "my skill isn't firing correctly", or want to convert a workflow/conversation into a reusable skill. Invoke proactively when a conversation has produced a repeatable workflow worth capturing. If the user mentions SKILL.md, skill files, skill descriptions, or skill triggering, this skill applies.
Decompose Return on Equity into component ratios to identify performance drivers. Use for financial analysis, performance benchmarking, and identifying improvement opportunities.
Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
Calculate engagement rates for creator posts and benchmark them against platform and tier averages. This skill should be used when calculating an influencer's engagement rate, benchmarking creator engagement against industry averages, evaluating whether a creator's engagement is above or below average for their tier, comparing engagement rates across platforms, checking if engagement rates suggest fake followers, auditing a creator's engagement quality before a partnership, analyzing engagement by content type (reels, stories, feed posts, TikTok videos), or assessing engagement trends across a creator's recent posts. For estimating fair market rates based on engagement, see creator-rate-estimator. For full creator vetting beyond engagement, see creator-vetting-scorecard. For scoring niche fit, see niche-fit-scorer.
Use this skill when benchmarking compensation, designing equity plans, building leveling frameworks, or structuring total rewards. Triggers on compensation benchmarking, equity grants, stock options, leveling, pay bands, total rewards, salary ranges, and any task requiring compensation strategy or structure design.
Troubleshoot Golang programs systematically - find and fix the root cause. Use when encountering bugs, crashes, deadlocks, or unexpected behavior in Go code. Covers debugging methodology, common Go pitfalls, test-driven debugging, pprof setup and capture, Delve debugger, race detection, GODEBUG tracing, and production debugging. Start here for any 'something is wrong' situation. Not for interpreting profiles or benchmarking (see golang-benchmark skill) or applying optimization patterns (see golang-performance skill).
Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).